Nature

Extremal Graph Theory and Spectral Analysis

Extremal graph theory seeks to determine the maximum or minimum values of graph invariants—such as edge count, degree sequence or subgraph density—subject to the exclusion of particular configurations ...
IEEE

Spatial–Spectral Bipartite Graph Clustering With Low-Frequency Tensor Regularization for Hyperspectral and LiDAR Data

Abstract: The increasing complexity of remote sensing (RS) applications necessitates multimodal data fusion to overcome the inherent limitations of single-source data. In particular, the integration ...
GitHub

ancastillar/spectral_clustering_tutorial

In this repository, you will find two files that will help you understand the Spectral Clustering algorithm: Implementation code: This file contains an example using a synthetic dataset that is not ...
IEEE

Adaptive Spectral Graph Attention Filtering Network for Alzheimer's Disease Classification Using Multimodal Data

Abstract: Early detection of Alzheimer's Disease (AD) is critical for timely intervention and management. However, existing graph-based approaches often fail to fully leverage the rich spectral-domain ...
GitHub

Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting

@article{jin2025expressive, title={Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting}, author={Ming Jin and Guangsi Shi and Yuan-Fang Li and Bo Xiong and Tian Zhou ...